Asymptotic variance expressions for closed-loop identification

DOI10.1016/S0005-1098(01)00015-2zbMath1153.93520OpenAlexW2018440729WikidataQ59591969 ScholiaQ59591969MaRDI QIDQ5936372

Michel Gevers, Lennart Ljung, Van den Hof, Paul M. J.

Publication date: 16 January 2002

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0005-1098(01)00015-2

zbMATH Keywords

System identificationAsymptotic variance expressions, Prediction error methodsClosed-loop identificationModel-based control design

Mathematics Subject Classification ID

Design techniques (robust design, computer-aided design, etc.) (93B51) Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)

Related Items (16)

Information matrix and D-optimal design with Gaussian inputs for Wiener model identification ⋮ A general multirate approach for direct closed-loop identification to the Nyquist frequency and beyond ⋮ Closed-loop identification of power system based on ambient data ⋮ A virtual closed loop method for closed loop identification ⋮ On the accuracy in errors-in-variables identification compared to prediction-error identification ⋮ Variance error, interpolation and experiment design ⋮ Covariance analysis in SISO linear systems identification ⋮ Closed‐Loop Identification for Control of Linear Parameter Varying Systems ⋮ On the frequency domain accuracy of closed-loop estimates ⋮ Analysis of the variability of joint input-output estimation methods ⋮ From experiment design to closed-loop control ⋮ Reduced-order controller design via iterative identification and control ⋮ Variance-error quantification for identified poles and zeros ⋮ Stability assessment for cautious iterative controller tuning ⋮ Closed-loop identification with an unstable or nonminimum phase controller ⋮ Model validation for control and controller validation in a prediction error identification framework. II: Illustrations

Cites Work

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• An indirect method for transfer function estimation from closed loop data
• Closed-loop identification with an unstable or nonminimum phase controller
• Identification and control -- Closed-loop issues
• A new approach to adaptive robust control
• The fundamental role of general orthonormal bases in system identification

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